read: value chain.

Reads the value chain of one vertical, with the brand whose participants are placed on it to The answer gives the chain's stocks and handovers with their counts, the participants on each stock, and the loops the templates name over it

Request body#

The request body is ValueChainInput.

Response#

The route returns a card whose body is ValueChain. Every card ends with a foot that states the basis of each number, the scope of the call, and the time when the facts were true.

Headers#

A caller needs the brand rung and a token with the read grant. The platform or the desktop app serves this route.

Example#

The example sends the smallest body that ValueChainInput allows. The build validates it against the schema of ValueChainInput.

curl -X POST https://api.scaleintelligence.co/v1/read/value_chain \
  -H "Scale-Key: $SCALE_KEY" -H "Scale-Scope: tenant/<id>" \
  -H "content-type: application/json" \
  -d '{ "vertical": "…" }'

import { client } from "@scale/sdk";
const answer = await client.read.value_chain({
    "vertical": "…"
  });
// answer.body is a ValueChain. answer.foot holds the basis, the scope and the time.

import requests
answer = requests.post("https://api.scaleintelligence.co/v1/read/value_chain",
    headers={"Scale-Key": KEY, "Scale-Scope": "tenant/<id>"},
    json={
      "vertical": "…"
    }).json()

let answer: Card = client.post("https://api.scaleintelligence.co/v1/read/value_chain")
    .header("Scale-Key", key).header("Scale-Scope", "tenant/<id>")
    .json(&ValueChainInput { /* the fields of the page */ }).send().await?.json().await?;

MCP tool#

The MCP tool si.read.value_chain takes the same input and returns the same card. The tool only reads data. An MCP host that renders cards draws this card from ui://scale-intelligence/cards/ValueChain. The tool’s page describes it.

POST /v1/read/value_chain
Scale-Scope: …
Scale-As-True-On: …
Scale-As-Known-On: …
Scale-Key: …
content-type: application/json

{
  "vertical": "…"
}